AI Medical Compendium Journal:
Molecules (Basel, Switzerland)

Showing 41 to 50 of 243 articles

Machine Learning Methods as a Cost-Effective Alternative to Physics-Based Binding Free Energy Calculations.

Molecules (Basel, Switzerland)
The rank ordering of ligands remains one of the most attractive challenges in drug discovery. While physics-based in silico binding affinity methods dominate the field, they still have problems, which largely revolve around forcefield accuracy and sa...

Artificial Intelligence Sensing: Effective Flavor Blueprinting of Tea Infusions for a Quality Control Perspective.

Molecules (Basel, Switzerland)
Tea infusions are the most consumed beverages in the world after water; their pleasant yet peculiar flavor profile drives consumer choice and acceptance and becomes a fundamental benchmark for the industry. Any qualification method capable of objecti...

Mechanochemical Degradation of Biopolymers.

Molecules (Basel, Switzerland)
Mechanochemical treatment of various organic molecules is an emerging technology of green processes in biofuel, fine chemicals, or food production. Many biopolymers are involved in isolating, derivating, or modifying molecules of natural origin. Mech...

Intelligent Protein Design and Molecular Characterization Techniques: A Comprehensive Review.

Molecules (Basel, Switzerland)
In recent years, the widespread application of artificial intelligence algorithms in protein structure, function prediction, and de novo protein design has significantly accelerated the process of intelligent protein design and led to many noteworthy...

LCK-SafeScreen-Model: An Advanced Ensemble Machine Learning Approach for Estimating the Binding Affinity between Compounds and LCK Target.

Molecules (Basel, Switzerland)
The lymphocyte-specific protein tyrosine kinase (LCK) is a critical target in leukemia treatment. However, potential off-target interactions involving LCK can lead to unintended consequences. This underscores the importance of accurately predicting t...

Integration of Deep Learning and Sequential Metabolism to Rapidly Screen Dipeptidyl Peptidase (DPP)-IV Inhibitors from .

Molecules (Basel, Switzerland)
Traditional Chinese medicine (TCM) possesses unique advantages in the management of blood glucose and lipids. However, there is still a significant gap in the exploration of its pharmacologically active components. Integrated strategies encompassing ...

Deep-Learning-Based Mixture Identification for Nuclear Magnetic Resonance Spectroscopy Applied to Plant Flavors.

Molecules (Basel, Switzerland)
Nuclear magnetic resonance (NMR) is a crucial technique for analyzing mixtures consisting of small molecules, providing non-destructive, fast, reproducible, and unbiased benefits. However, it is challenging to perform mixture identification because o...

Exploring the World of Membrane Proteins: Techniques and Methods for Understanding Structure, Function, and Dynamics.

Molecules (Basel, Switzerland)
In eukaryotic cells, membrane proteins play a crucial role. They fall into three categories: intrinsic proteins, extrinsic proteins, and proteins that are essential to the human genome (30% of which is devoted to encoding them). Hydrophobic interacti...

Naive Prediction of Protein Backbone Phi and Psi Dihedral Angles Using Deep Learning.

Molecules (Basel, Switzerland)
Protein structure prediction represents a significant challenge in the field of bioinformatics, with the prediction of protein structures using backbone dihedral angles recently achieving significant progress due to the rise of deep neural network re...

Machine Learning Techniques Applied to the Study of Drug Transporters.

Molecules (Basel, Switzerland)
With the advancement of computer technology, machine learning-based artificial intelligence technology has been increasingly integrated and applied in the fields of medicine, biology, and pharmacy, thereby facilitating their development. Transporters...